1. Field of the Invention
Embodiments of the present invention are drawn to systems, methods, and media, recognizing patterns and providing appropriate responses, and more specifically, to systems, methods, and media harmonizing implicit usage pattern analysis for portable devices, potentially with explicit user input, in order to adaptively recognize and/or anticipate a user's desired action based on a detected pattern extracted from correlated data and the potential user input after deployment of the portable devices.
2. Description of the Related Art
Previously, portable devices were primarily for performing core operations, e.g., operating as a telephone in mobile phones, scheduling/addressing in personal data assistants (PDAs), or data processing in mobile computer, e.g., laptops. Inherently the mobile computers have greater capabilities than mobile phones or PDAs, but recently all types of portable devices have been incorporating greater and greater numbers of none core capabilities. For example, mobile phones have incorporated calendar functions, text messaging, email functionality, and multimedia interactivity. Similarly, PDAs may be able to perform such operations, as well as some operations of the mobile phones, e.g., telephone operations. Similarly, mobile computers are also now incorporating mobile telecommunication capabilities, such as wireless LAN and mobile internet communication. Thus, there is now somewhat of a synergy between the portable devices, providing greater capabilities, based mostly on the available processing power of each device and corresponding power supply constraints.
However, with these additional capabilities unanticipated problems have arisen. Primarily, because of the portable nature of these devices, differing internal and external environmental conditions/events are encroaching on the benefits of having the additional capabilities or at least making the lack of interoperation between the separate capabilities more noticed. For example, though a mobile phone may have variable ring setting levels, e.g., outside, inside, or meeting, there is no way to enable an automated setting of the different ring preferences and instituting of the change from one setting to another based on an internal or external environmental condition/event, i.e., there is no automated way to set a ring preference and there is no automated way to subsequently institute the change. Essentially, the addition of all the capabilities to the portable devices has actually created additional problems in that there is no current automated way to integrate the different capabilities.
As noted above, conventionally, most user interactions with these additional capabilities, e.g., a particular operation happening based upon a particular item in an address book or calendar or a mobile phone's ring volume being based on user location, have only been modifiable based on an initiation from a user. The user, or manufacture, must set initial preferences and linkages between the different capabilities/applications in the portable device and desired operations. Thus, if a user typically enters a meeting at a certain time identified in a calendar and desires the mobile phone ring tone to be set to ‘meeting’ (perhaps vibration only), then the user has to initiate the setting of the user settings. Then, the operation of that user setting will continue until the user changes the setting. Similarly, if the physical location of the user is determined to have changed, e.g., the user has left the meeting, there is no automated way to set up a desired changing of the phone ringer back to a normal or non-meeting setting. The user must initiate the setting of such a change.
Thus, there is no current way for a portable device to learn before and after deployment/setting. Currently, portable devices must be taught before deployment, i.e., during manufacture or by a user before occurrence of the aforementioned environmental conditions, i.e., currently there is no proactive learning and there is no corresponding automated initiation of operations based on that learning. Therefore, embodiments of the present invention solve for at least this deficiency for portable devices by implementing a pattern analysis of the portable device's operations and automating an initiation of operations based on the pattern analysis.